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Published in:
2007 | OriginalPaper | Chapter
Keyphrase Extraction in Scientific Publications
Authors : Thuy Dung Nguyen, Min-Yen Kan
Published in: Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers
Publisher: Springer Berlin Heidelberg
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We present a keyphrase extraction algorithm for scientific publications. Different from previous work, we introduce features that capture the positions of phrases in document with respect to logical sections found in scientific discourse. We also introduce features that capture salient morphological phenomena found in scientific keyphrases, such as whether a candidate keyphrase is an acronyms or uses specific terminologically productive suffixes. We have implemented these features on top of a baseline feature set used by Kea [1]. In our evaluation using a corpus of 120 scientific publications multiply annotated for keyphrases, our system significantly outperformed Kea at the
p
< .05 level. As we know of no other existing multiply annotated keyphrase document collections, we have also made our evaluation corpus publicly available. We hope that this contribution will spur future comparative research.